python - Combine two pandas dataframes adding corresponding values -

i have 2 dataframes these:

df1 = pd.dataframe({'a': [1,0,3], 'b':[0,0,1], 'c':[0,2,2]}, index =['a','b','c']) df2 = pd.dataframe({'a': [0,0], 'b':[2,1]}, index =['a','c']) 

df1 , df2:

   | | b | c |          | | b |     ---|---|---|---|       ---|---|---|  | 1 | 0 | 0 |        | 0 | 2 |     b | 0 | 0 | 2 |        c | 0 | 1 |  c | 3 | 1 | 2 | 

and expected result is:

   | | b | c | ---|---|---|---|  | 1 | 2 | 0 |  b | 0 | 0 | 2 |  c | 3 | 2 | 2 | 

i'm having problems because there may missing columns/rows in of dataframes (df1 may not have columns , rows df2 has)

going idea in answer question - merge 2 dataframes in pandas: join on columns, sum others

since in case, indexes ones common, can use pandas.concat() 2 dataframes, dataframe.groupby based on index, , take sum on it. example -

in [27]: df1 out[27]:     b  c  1  0  0 b  0  0  2 c  3  1  2  in [28]: df2 out[28]:     b  0  2 c  0  1  in [29]: pd.concat([df1,df2]).groupby(level=0).sum() out[29]:     b  c  1  2  0 b  0  0  2 c  3  2  2